sd-webui-controlnet
multidiffusion-upscaler-for-automatic1111
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sd-webui-controlnet | multidiffusion-upscaler-for-automatic1111 | |
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247 | 83 | |
15,859 | 4,444 | |
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9.7 | 7.8 | |
6 days ago | 30 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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sd-webui-controlnet
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OpenPose ControlNet: A Beginner's Guide
A crucial step for achieving stable diffusion controlnet settings is the installation of the controlnet extension in Google Colab. Whether on a Windows PC or Mac, installing controlnet is vital for stable diffusion of human pose details. Additionally, updating the controlnet extension is necessary to maintain stability and achieve the desired results in OpenPose model. To install the v1.1 controlnet extension, go to the “extensions” tab and install it from this URL: https://github.com/Mikubill/sd-webui-controlnet. If you already have v1 controlnets installed, delete the folder from stable-diffusion-webui/extensions/. Install the v1.
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StyleAligned node for ComfyUI
1.1.420 Image-wise ControlNet and StyleAlign
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PATCHFUSION is really impressive. High resolution depth maps in 16bit. I've been waiting for this. https://github.com/zhyever/PatchFusion
I opened a request thread on ControlNet GitHub you can give a support : https://github.com/Mikubill/sd-webui-controlnet/issues/2319
- Going to lose my mind at this point with this problem
- Samples of style-aligned
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Is it possible to outpaint with SD or SDXL as easy as with photoshop? (no prompts)
It has been possible for 7 months now
- Reference Only Broken (Can someone with a working Reference Only CN upload there extension folder)
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Web app prototype to create controlnet segmentation maps for Stable Diffusion
I sometimes use a very similar technique in Cinema4d (here is a link to a c4d file with preset materials referencing proper colors for Semantic Segmentation if any other c4d user wants to try it), but yours is a much more accessible solution as it's free and it's accessible online.
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Dalle-3 Examples
There are models available that give you more control - in some senses, at least.
For example, you can use Stable Diffusion with 'ControlNet' [1] where for example, you can input an 'openpose' to choose the pose of people in the scene.
There's also a 'Regional Prompter' [2] which lets you use different prompts for different areas of the image, giving you some control over the composition.
You can also use 'inpainting' to regenerate select parts of your image if, for example, you don't like the shape of the clouds.
Of course this stuff isn't perfect - for example, you'll get hands with the wrong number of fingers sometimes, no matter what you specify :)
[1] https://github.com/Mikubill/sd-webui-controlnet
- ControlNet SDXL for Automatic1111-WebUI official release: sd-webui-controlnet 1.1.400
multidiffusion-upscaler-for-automatic1111
- Stable Diffusion can't stop generating extra torsos, even with negative prompt. Any suggestions?
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Reduce Or Remove The Use Of RAM In Image Generation
Use tiled VAE, it will save VRAM: pkuliyi2015/multidiffusion-upscaler-for-automatic1111: Tiled Diffusion and VAE optimize, licensed under CC BY-NC-SA 4.0 (github.com)
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How I do I fix these boxes/lines appearing while using Ultimate SD upscale + CN tiles? All the details are in my comment below. Please Helps. MANY THANKS !!!
My favorite solution is to not use ultimate Sd upscale and instead use multidiffusion-upscaler.
- Is there any way to purge the VRAM of your card after getting OOT'ed other than restarting the Web UI?
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Not able to generate more than 400*400 image
sure, i personally use 'tiled diffusion' https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111, works like charm also use adetailer for faces if its needed.
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GTX 1070 slow render speeds
What worked for my 1080 was using TiledVAE and turning down the quality of my previews - I don't pay much attention to it/s but it's definitely faster than using --medvram, and now I can handle batches and large resolutions without things exploding on me.
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Initial release of A8R8 (Alternate Reality), an opinionated interface for Stable Diffusion image generation, works with A1111. Docker installation included. Open source and runs locally!
I would highly recommend adding https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111 to your A1111 installation, TiledVAE is enabled automatically under the hood in A8R8; this will allow you to get even larger generations before getting an out of memory error. You'll get a Tiled Diffusion checkbox with some reasonable hardcoded defaults as well.
- I love the Tile ControlNet, but it's really easy to overdo. Look at this monstrosity of tiny detail I made by accident.
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Can you generate 2048x2048 images with an 8GB GPU?
Use Tiled VAE https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111
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SDXL 0.9 vs SD 2.1 vs SD 1.5 (All base models) - Batman taking a selfie in a jungle, 4k
That's weird. 10GB should allow you to hires to 2048x2048 at least. Use Tiled VAE extension https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111 that will allow you to go even beyond that.
What are some alternatives?
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
ultimate-upscale-for-automatic1111
openpose-editor - Openpose Editor for AUTOMATIC1111's stable-diffusion-webui
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
T2I-Adapter - T2I-Adapter
ComfyUI_TiledKSampler - Tiled samplers for ComfyUI
ControlNet - Let us control diffusion models!
Waifu2x-Extension-GUI - Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, RTX Video Super Resolution VSR, SRMD, RealSR, Anime4K, RIFE, IFRNet, CAIN, DAIN, and ACNet.
stable-diffusion-webui-colab - stable diffusion webui colab
mixture-of-diffusers - Mixture of Diffusers for scene composition and high resolution image generation
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-two-shot - Latent Couple extension (two shot diffusion port)